Sentiment analysis

Sentiment analysis aims to determine the positive, negative, and neutral polarities of subjective sentences. By analyzing the content of a text unit, it is possible to estimate the emotional state of the author when writing the text and the effect he or she wants to have on the readers. Sentiment analysis on the Pega 7 Platform is achieved by means of lexicons and sentiment models.

• Lexicons - They are lists of words and their associated sentiment. By identifying the sentiments of the individual words or phrases, it is possible to estimate the general sentiment of a text unit. Lexicons are defined for each supported language separately and stored as decision data records.
• Sentiment models - They contain algorithms that can act on particular elements of a text unit as well as on the whole text.

Each sentence that undergoes sentiment analysis gets a sentiment score between -1 and 1. The individual scores of all sentences are used to calculate the overall sentiment of the text unit. You can specify the score range for the positive, negative, and neutral sentiment.

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